mirror of
https://github.com/meta-llama/llama-stack.git
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116 lines
4.2 KiB
Python
116 lines
4.2 KiB
Python
# Copyright (c) Meta Platforms, Inc. and affiliates.
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# All rights reserved.
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#
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# This source code is licensed under the terms described in the LICENSE file in
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# the root directory of this source tree.
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import json
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import logging
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from typing import Any, Dict, List
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import boto3
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from llama_stack.apis.safety import * # noqa
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from llama_models.llama3.api.datatypes import * # noqa: F403
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from .config import BedrockSafetyConfig
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logger = logging.getLogger(__name__)
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BEDROCK_SUPPORTED_SHIELDS = [
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ShieldType.generic_content_shield.value,
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]
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class BedrockSafetyAdapter(Safety):
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def __init__(self, config: BedrockSafetyConfig) -> None:
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if not config.aws_profile:
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raise ValueError(f"Missing boto_client aws_profile in model info::{config}")
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self.config = config
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self.registered_shields = []
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async def initialize(self) -> None:
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try:
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print(f"initializing with profile --- > {self.config}")
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self.boto_client = boto3.Session(
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profile_name=self.config.aws_profile
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).client("bedrock-runtime")
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except Exception as e:
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raise RuntimeError("Error initializing BedrockSafetyAdapter") from e
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async def shutdown(self) -> None:
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pass
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async def register_shield(self, shield: ShieldDef) -> None:
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if shield.type not in BEDROCK_SUPPORTED_SHIELDS:
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raise ValueError(f"Unsupported safety shield type: {shield.type}")
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shield_params = shield.params
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if "guardrailIdentifier" not in shield_params:
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raise ValueError(
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"Error running request for BedrockGaurdrails:Missing GuardrailID in request"
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)
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if "guardrailVersion" not in shield_params:
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raise ValueError(
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"Error running request for BedrockGaurdrails:Missing guardrailVersion in request"
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)
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async def run_shield(
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self, shield_type: str, messages: List[Message], params: Dict[str, Any] = None
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) -> RunShieldResponse:
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shield_def = await self.shield_store.get_shield(shield_type)
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if not shield_def:
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raise ValueError(f"Unknown shield {shield_type}")
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"""This is the implementation for the bedrock guardrails. The input to the guardrails is to be of this format
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```content = [
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{
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"text": {
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"text": "Is the AB503 Product a better investment than the S&P 500?"
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}
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}
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]```
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However the incoming messages are of this type UserMessage(content=....) coming from
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https://github.com/meta-llama/llama-models/blob/main/models/llama3/api/datatypes.py
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They contain content, role . For now we will extract the content and default the "qualifiers": ["query"]
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"""
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shield_params = shield_def.params
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logger.debug(f"run_shield::{shield_params}::messages={messages}")
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# - convert the messages into format Bedrock expects
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content_messages = []
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for message in messages:
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content_messages.append({"text": {"text": message.content}})
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logger.debug(
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f"run_shield::final:messages::{json.dumps(content_messages, indent=2)}:"
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)
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response = self.boto_client.apply_guardrail(
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guardrailIdentifier=shield_params["guardrailIdentifier"],
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guardrailVersion=shield_params["guardrailVersion"],
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source="OUTPUT", # or 'INPUT' depending on your use case
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content=content_messages,
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)
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if response["action"] == "GUARDRAIL_INTERVENED":
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user_message = ""
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metadata = {}
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for output in response["outputs"]:
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# guardrails returns a list - however for this implementation we will leverage the last values
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user_message = output["text"]
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for assessment in response["assessments"]:
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# guardrails returns a list - however for this implementation we will leverage the last values
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metadata = dict(assessment)
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return SafetyViolation(
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user_message=user_message,
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violation_level=ViolationLevel.ERROR,
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metadata=metadata,
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)
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return None
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